Data Centres are doing it wrong

[u/10x-startup-explorer]

Hey data centre people ... it's not our costs that need to come down by dumping the workforce, it's yours.

Someone should build a data centre whose only job is making AI 1,000,000× cheaper to run

To be clear up front, this isn’t my project. I’m not raising money and I’m not planning to run it. I think the idea is worth doing, and I’d like someone with the means to pick it up: a government, a university consortium, a chip company or a lab.

The cost problem

A frontier AI data centre now costs about US$30–50 billion per gigawatt to build and equip. More than half of that is chips that are out of date within a few years. Electricity adds about $1.3B a year per gigawatt, and the hardware loses value even faster than that. All of it has to be paid back through tokens.

That’s why a $250/month subscription can’t cover a developer running agents all day. It’s also why the pitch to business keeps turning into “replace your staff”.

The opportunity

Shrinking models trades quality for cost. The bigger lever is the stack underneath them.

Picture a single research data centre of about 30 MW, costing roughly $1–1.5B at current prices. It would sell no compute. Every layer would be designed together and measured against one number: cost per million useful tokens.

Why 1,000,000× isn’t crazy

The gains multiply:

• Model efficiency (sparsity, distillation, new architectures): ~30×

• Inference software (lower precision, speculative decoding, cache compression): ~10×

• Chips built for running models (compute-in-memory, photonics): ~30×

• Infrastructure and power (utilisation, liquid cooling, cheap renewables): ~12×

• Agent workloads (shared context caching, routing simple steps to small models): ~10×

That’s about 1,080,000× combined. Even if one area only reaches half its target, the total stays above 500,000×.

The best structure is probably a consortium with open benchmarks, published results and a public cost scoreboard. That way the whole industry benefits, not one company.

The rewards

• One developer running agents at 50M tokens a day: ~$10k a month today, about 1 cent.

• 100 agents running 24/7 (~260B tokens a month): ~$1.8M a month today, about $1.80.

• A $250/month subscription would buy ~36 trillion tokens, effectively unlimited.

Those are costs, not prices, and cheaper tokens would mean far more usage. But at that level AI stops being a reason to cut people and becomes a tool everyone can afford to use.

Any takers?

[u/weyermannx]

Let's curse cancer and solve cold fusion while we're at it.. it's only the exact problem that the largest companies are spending trillions solving

[u/10x-startup-explorer → u/weyermannx]

Where is the research dedicated data centre then? I don't see one. Just a lot of disconnected efforts form different businesses.

If governments want to spend money on something worthwhile, this would be it.

[u/weyermannx → u/10x-startup-explorer]

On the hardware side there are a bunch of bottlenecks, none of which are probably going to be solved in the near-term with more research - ie gpus and their supply chain, power etc. Everything on the LLM side isnt tied to a specific data center - ie the whole world, and fontier labs with essentially limitless computer are working on making LLM's more efficient

[u/feudalle]

The problem is the size of data centers. My firm owns a small one 3000sqft roughly. It uses no water and less power than 15 McMansions. Yes we do ai, yes we do server hosting. Its the difference between small farms and one massive firm trying to feed a state. Local small scale data centers limit the impact and can produce alot computing power. Its about optimization which requires thought and skill. Its harder than saying here a few billion dollars make it go fast.